{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "EfficientNetV2 TF2 with tf-hub",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oYM61xrTsP5d"
      },
      "source": [
        "# EfficientNetV2 with tf-hub\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MfBg1C5NB3X0"
      },
      "source": [
        "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
        "<td>\n",
        "  <a target=\"_blank\"  href=\"https://github.com/google/automl/blob/master/efficientnetv2/tfhub.ipynb\">\n",
        "    <img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on github\n",
        "  </a>\n",
        "</td><td>\n",
        "  <a target=\"_blank\"  href=\"https://colab.sandbox.google.com/github/google/automl/blob/master/efficientnetv2/tfhub.ipynb\">\n",
        "    <img width=32px src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
        "</td><td>\n",
        "    <!----<a href=\"https://tfhub.dev/google/collections/image/1\"><img src=\"https://www.tensorflow.org/images/hub_logo_32px.png\" />TF Hub models</a>--->\n",
        "  </td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L1otmJgmbahf"
      },
      "source": [
        "## 1.Introduction\n",
        "\n",
        "[EfficientNetV2](https://arxiv.org/abs/2104.00298) is a family of classification models, with better accuracy, smaller size, and faster speed than previous models.\n",
        "\n",
        "\n",
        "This doc describes some examples with EfficientNetV2 tfhub. For more details, please visit the official code: https://github.com/google/automl/tree/master/efficientnetv2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mmaHHH7Pvmth"
      },
      "source": [
        "## 2.Select the TF2 SavedModel module to use"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FlsEcKVeuCnf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a81e6d95-2d0c-4625-e25e-e62cbd753558"
      },
      "source": [
        "import itertools\n",
        "import os\n",
        "\n",
        "import matplotlib.pylab as plt\n",
        "import numpy as np\n",
        "\n",
        "import tensorflow as tf\n",
        "import tensorflow_hub as hub\n",
        "\n",
        "print('TF version:', tf.__version__)\n",
        "print('Hub version:', hub.__version__)\n",
        "print('Phsical devices:', tf.config.list_physical_devices())\n",
        "\n",
        "def get_hub_url_and_isize(model_name, ckpt_type, hub_type):\n",
        "  if ckpt_type == '-1k':\n",
        "    ckpt_type = ''  # json doesn't support empty string\n",
        "  \n",
        "  hub_url_map = {\n",
        "    'efficientnetv2-b0': f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-b0/{hub_type}',\n",
        "    'efficientnetv2-b1': f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-b1/{hub_type}',\n",
        "    'efficientnetv2-b2': f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-b2/{hub_type}',\n",
        "    'efficientnetv2-b3': f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-b3/{hub_type}',\n",
        "    'efficientnetv2-s':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-s/{hub_type}',\n",
        "    'efficientnetv2-m':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-m/{hub_type}',\n",
        "    'efficientnetv2-l':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-l/{hub_type}',\n",
        "    'efficientnetv2-s-21k':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-s-21k/{hub_type}',\n",
        "    'efficientnetv2-m-21k':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-m-21k/{hub_type}',\n",
        "    'efficientnetv2-l-21k':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-l-21k/{hub_type}',\n",
        "    'efficientnetv2-s-21k-ft1k':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-s-21k-ft1k/{hub_type}',\n",
        "    'efficientnetv2-m-21k-ft1k':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-m-21k-ft1k/{hub_type}',\n",
        "    'efficientnetv2-l-21k-ft1k':  f'gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-l-21k-ft1k/{hub_type}',\n",
        "      \n",
        "    # efficientnetv1\n",
        "    'efficientnet_b0': f'https://tfhub.dev/tensorflow/efficientnet/b0/{hub_type}/1',\n",
        "    'efficientnet_b1': f'https://tfhub.dev/tensorflow/efficientnet/b1/{hub_type}/1',\n",
        "    'efficientnet_b2': f'https://tfhub.dev/tensorflow/efficientnet/b2/{hub_type}/1',\n",
        "    'efficientnet_b3': f'https://tfhub.dev/tensorflow/efficientnet/b3/{hub_type}/1',\n",
        "    'efficientnet_b4': f'https://tfhub.dev/tensorflow/efficientnet/b4/{hub_type}/1',\n",
        "    'efficientnet_b5': f'https://tfhub.dev/tensorflow/efficientnet/b5/{hub_type}/1',\n",
        "    'efficientnet_b6': f'https://tfhub.dev/tensorflow/efficientnet/b6/{hub_type}/1',\n",
        "    'efficientnet_b7': f'https://tfhub.dev/tensorflow/efficientnet/b7/{hub_type}/1',\n",
        "  }\n",
        "  \n",
        "  image_size_map = {\n",
        "    'efficientnetv2-b0': 224,\n",
        "    'efficientnetv2-b1': 240,\n",
        "    'efficientnetv2-b2': 260,\n",
        "    'efficientnetv2-b3': 300,\n",
        "    'efficientnetv2-s':  384,\n",
        "    'efficientnetv2-m':  480,\n",
        "    'efficientnetv2-l':  480,\n",
        "  \n",
        "    'efficientnet_b0': 224,\n",
        "    'efficientnet_b1': 240,\n",
        "    'efficientnet_b2': 260,\n",
        "    'efficientnet_b3': 300,\n",
        "    'efficientnet_b4': 380,\n",
        "    'efficientnet_b5': 456,\n",
        "    'efficientnet_b6': 528,\n",
        "    'efficientnet_b7': 600,\n",
        "  }\n",
        "  \n",
        "  hub_url = hub_url_map.get(model_name + ckpt_type)\n",
        "  image_size = image_size_map.get(model_name, 224)\n",
        "  return hub_url, image_size\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "TF version: 2.5.0\n",
            "Hub version: 0.12.0\n",
            "Phsical devices: [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU'), PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "REiLDGq_W5FA"
      },
      "source": [
        "## 3.Inference with Panda image"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E32RGKBEWq76",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 799
        },
        "outputId": "1d635114-509e-4b52-86c0-befd5573b4c9"
      },
      "source": [
        "# Build model\n",
        "import tensorflow_hub as hub\n",
        "model_name = 'efficientnetv2-s' #@param {type:'string'}\n",
        "ckpt_type = '-21k-ft1k'   # @param ['-21k', '-21k-ft1k', '-1k']\n",
        "hub_type = 'classification' # @param ['classification', 'feature-vector']\n",
        "hub_url, image_size = get_hub_url_and_isize(model_name, ckpt_type, hub_type)\n",
        "tf.keras.backend.clear_session()\n",
        "m = hub.KerasLayer(hub_url, trainable=False)\n",
        "m.build([None, 224, 224, 3])  # Batch input shape.\n",
        "\n",
        "# Download label map file and image\n",
        "labels_map = '/tmp/labels_map.txt'\n",
        "image_file = '/tmp/panda.jpg'\n",
        "tf.keras.utils.get_file(image_file, 'https://upload.wikimedia.org/wikipedia/commons/f/fe/Giant_Panda_in_Beijing_Zoo_1.JPG')\n",
        "tf.keras.utils.get_file(labels_map, 'https://storage.googleapis.com/cloud-tpu-checkpoints/efficientnet/eval_data/labels_map.txt')\n",
        "\n",
        "# preprocess image.\n",
        "image = tf.keras.preprocessing.image.load_img(image_file, target_size=(224, 224))\n",
        "image = tf.keras.preprocessing.image.img_to_array(image)\n",
        "image = (image - 128.) / 128.\n",
        "logits = m(tf.expand_dims(image, 0), False)\n",
        "\n",
        "# Output classes and probability\n",
        "pred = tf.keras.layers.Softmax()(logits)\n",
        "idx = tf.argsort(logits[0])[::-1][:5].numpy()\n",
        "import ast\n",
        "classes = ast.literal_eval(open(labels_map, \"r\").read())\n",
        "for i, id in enumerate(idx):\n",
        "  print(f'top {i+1} ({pred[0][id]*100:.1f}%):  {classes[id]} ')\n",
        "from IPython import display\n",
        "display.display(display.Image(image_file))"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://upload.wikimedia.org/wikipedia/commons/f/fe/Giant_Panda_in_Beijing_Zoo_1.JPG\n",
            "122880/116068 [===============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/cloud-tpu-checkpoints/efficientnet/eval_data/labels_map.txt\n",
            "32768/30565 [================================] - 0s 0us/step\n",
            "top 1 (95.1%):  giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca \n",
            "top 2 (0.1%):  indri, indris, Indri indri, Indri brevicaudatus \n",
            "top 3 (0.1%):  lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens \n",
            "top 4 (0.1%):  king snake, kingsnake \n",
            "top 5 (0.1%):  skunk, polecat, wood pussy \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yTY8qzyYv3vl"
      },
      "source": [
        "## 4.Finetune with Flowers dataset."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c_12xwDuZFOQ"
      },
      "source": [
        "Get hub_url and image_size\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "50FYNIb1dmJH"
      },
      "source": [
        "# Build model\n",
        "import tensorflow_hub as hub\n",
        "model_name = 'efficientnetv2-b0' #@param {type:'string'}\n",
        "ckpt_type = '-1k'   # @param ['-21k', '-21k-ft1k', '-1k']\n",
        "hub_type = 'feature-vector' # @param ['feature-vector']\n",
        "batch_size =  32#@param {type:\"integer\"}\n",
        "hub_url, image_size = get_hub_url_and_isize(model_name, ckpt_type, hub_type)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lus9bIA-bQgj"
      },
      "source": [
        "Get dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "umB5tswsfTEQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8df0490e-13cd-4de4-fa0a-a6551ecdb6d5"
      },
      "source": [
        "data_dir = tf.keras.utils.get_file(\n",
        "    'flower_photos',\n",
        "    'https://storage.googleapis.com/download.tensorflow.org/example_images/flower_photos.tgz',\n",
        "    untar=True)\n",
        "    \n",
        "datagen_kwargs = dict(rescale=1./255, validation_split=.20)\n",
        "dataflow_kwargs = dict(target_size=(image_size, image_size),\n",
        "                       batch_size=batch_size,\n",
        "                       interpolation=\"bilinear\")\n",
        "\n",
        "valid_datagen = tf.keras.preprocessing.image.ImageDataGenerator(\n",
        "    **datagen_kwargs)\n",
        "valid_generator = valid_datagen.flow_from_directory(\n",
        "    data_dir, subset=\"validation\", shuffle=False, **dataflow_kwargs)\n",
        "\n",
        "do_data_augmentation = False #@param {type:\"boolean\"}\n",
        "if do_data_augmentation:\n",
        "  train_datagen = tf.keras.preprocessing.image.ImageDataGenerator(\n",
        "      rotation_range=40,\n",
        "      horizontal_flip=True,\n",
        "      width_shift_range=0.2, height_shift_range=0.2,\n",
        "      shear_range=0.2, zoom_range=0.2,\n",
        "      **datagen_kwargs)\n",
        "else:\n",
        "  train_datagen = valid_datagen\n",
        "train_generator = train_datagen.flow_from_directory(\n",
        "    data_dir, subset=\"training\", shuffle=True, **dataflow_kwargs)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/download.tensorflow.org/example_images/flower_photos.tgz\n",
            "228818944/228813984 [==============================] - 2s 0us/step\n",
            "Found 731 images belonging to 5 classes.\n",
            "Found 2939 images belonging to 5 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u2e5WupIw2N2"
      },
      "source": [
        "Training the model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9f3yBUvkd_VJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "99b79db6-d9f9-438e-9011-8221e8c5377c"
      },
      "source": [
        "# whether to finetune the whole model or just the top layer.\n",
        "do_fine_tuning = True #@param {type:\"boolean\"}\n",
        "num_epochs = 2 #@param {type:\"integer\"}\n",
        "\n",
        "tf.keras.backend.clear_session()\n",
        "model = tf.keras.Sequential([\n",
        "    # Explicitly define the input shape so the model can be properly\n",
        "    # loaded by the TFLiteConverter\n",
        "    tf.keras.layers.InputLayer(input_shape=[image_size, image_size, 3]),\n",
        "    hub.KerasLayer(hub_url, trainable=do_fine_tuning),\n",
        "    tf.keras.layers.Dropout(rate=0.2),\n",
        "    tf.keras.layers.Dense(train_generator.num_classes,\n",
        "                          kernel_regularizer=tf.keras.regularizers.l2(0.0001))\n",
        "])\n",
        "model.build((None, image_size, image_size, 3))\n",
        "model.summary()\n",
        "\n",
        "model.compile(\n",
        "  optimizer=tf.keras.optimizers.SGD(learning_rate=0.005, momentum=0.9), \n",
        "  loss=tf.keras.losses.CategoricalCrossentropy(from_logits=True, label_smoothing=0.1),\n",
        "  metrics=['accuracy'])\n",
        "\n",
        "steps_per_epoch = train_generator.samples // train_generator.batch_size\n",
        "validation_steps = valid_generator.samples // valid_generator.batch_size\n",
        "hist = model.fit(\n",
        "    train_generator,\n",
        "    epochs=num_epochs, steps_per_epoch=steps_per_epoch,\n",
        "    validation_data=valid_generator,\n",
        "    validation_steps=validation_steps).history"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "keras_layer (KerasLayer)     (None, 1280)              5919312   \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 1280)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 5)                 6405      \n",
            "=================================================================\n",
            "Total params: 5,925,717\n",
            "Trainable params: 5,865,109\n",
            "Non-trainable params: 60,608\n",
            "_________________________________________________________________\n",
            "Epoch 1/2\n",
            "91/91 [==============================] - 33s 243ms/step - loss: 0.9861 - accuracy: 0.7079 - val_loss: 0.6987 - val_accuracy: 0.8750\n",
            "Epoch 2/2\n",
            "91/91 [==============================] - 20s 219ms/step - loss: 0.6411 - accuracy: 0.9030 - val_loss: 0.6268 - val_accuracy: 0.9034\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oi1iCNB9K1Ai",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "outputId": "c8e2fc22-b4bd-4950-bce3-6c4af197f405"
      },
      "source": [
        "def get_class_string_from_index(index):\n",
        "   for class_string, class_index in valid_generator.class_indices.items():\n",
        "      if class_index == index:\n",
        "         return class_string\n",
        "\n",
        "x, y = next(valid_generator)\n",
        "image = x[0, :, :, :]\n",
        "true_index = np.argmax(y[0])\n",
        "plt.imshow(image)\n",
        "plt.axis('off')\n",
        "plt.show()\n",
        "\n",
        "# Expand the validation image to (1, 224, 224, 3) before predicting the label\n",
        "prediction_scores = model.predict(np.expand_dims(image, axis=0))\n",
        "predicted_index = np.argmax(prediction_scores)\n",
        "print(\"True label: \" + get_class_string_from_index(true_index))\n",
        "print(\"Predicted label: \" + get_class_string_from_index(predicted_index))"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "True label: daisy\n",
            "Predicted label: daisy\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YCsAsQM1IRvA"
      },
      "source": [
        "Finally, the trained model can be saved for deployment to TF Serving or TF Lite (on mobile) as follows."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LGvTi69oIc2d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "710b8803-3e34-4948-96e7-d905c5c96d64"
      },
      "source": [
        "saved_model_path = f\"/tmp/saved_flowers_model_{model_name}\"\n",
        "tf.saved_model.save(model, saved_model_path)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:absl:Found untraced functions such as restored_function_body, restored_function_body, restored_function_body, restored_function_body, restored_function_body while saving (showing 5 of 460). These functions will not be directly callable after loading.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:FOR KERAS USERS: The object that you are saving contains one or more Keras models or layers. If you are loading the SavedModel with `tf.keras.models.load_model`, continue reading (otherwise, you may ignore the following instructions). Please change your code to save with `tf.keras.models.save_model` or `model.save`, and confirm that the file \"keras.metadata\" exists in the export directory. In the future, Keras will only load the SavedModels that have this file. In other words, `tf.saved_model.save` will no longer write SavedModels that can be recovered as Keras models (this will apply in TF 2.5).\n",
            "\n",
            "FOR DEVS: If you are overwriting _tracking_metadata in your class, this property has been used to save metadata in the SavedModel. The metadta field will be deprecated soon, so please move the metadata to a different file.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:FOR KERAS USERS: The object that you are saving contains one or more Keras models or layers. If you are loading the SavedModel with `tf.keras.models.load_model`, continue reading (otherwise, you may ignore the following instructions). Please change your code to save with `tf.keras.models.save_model` or `model.save`, and confirm that the file \"keras.metadata\" exists in the export directory. In the future, Keras will only load the SavedModels that have this file. In other words, `tf.saved_model.save` will no longer write SavedModels that can be recovered as Keras models (this will apply in TF 2.5).\n",
            "\n",
            "FOR DEVS: If you are overwriting _tracking_metadata in your class, this property has been used to save metadata in the SavedModel. The metadta field will be deprecated soon, so please move the metadata to a different file.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Assets written to: /tmp/saved_flowers_model_efficientnetv2-b0/assets\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Assets written to: /tmp/saved_flowers_model_efficientnetv2-b0/assets\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QzW4oNRjILaq"
      },
      "source": [
        "## Optional: Deployment to TensorFlow Lite\n",
        "\n",
        "[TensorFlow Lite](https://www.tensorflow.org/lite) for mobile. Here we also runs tflite file in the TF Lite Interpreter to examine the resulting quality."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Va1Vo92fSyV6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "11956d83-1b22-4330-f57a-bfc893ec2b2a"
      },
      "source": [
        "optimize_lite_model = True  #@param {type:\"boolean\"}\n",
        "#@markdown Setting a value greater than zero enables quantization of neural network activations. A few dozen is already a useful amount.\n",
        "num_calibration_examples = 81  #@param {type:\"slider\", min:0, max:1000, step:1}\n",
        "representative_dataset = None\n",
        "if optimize_lite_model and num_calibration_examples:\n",
        "  # Use a bounded number of training examples without labels for calibration.\n",
        "  # TFLiteConverter expects a list of input tensors, each with batch size 1.\n",
        "  representative_dataset = lambda: itertools.islice(\n",
        "      ([image[None, ...]] for batch, _ in train_generator for image in batch),\n",
        "      num_calibration_examples)\n",
        "\n",
        "converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_path)\n",
        "if optimize_lite_model:\n",
        "  converter.optimizations = [tf.lite.Optimize.DEFAULT]\n",
        "  if representative_dataset:  # This is optional, see above.\n",
        "    converter.representative_dataset = representative_dataset\n",
        "lite_model_content = converter.convert()\n",
        "\n",
        "with open(f\"/tmp/lite_flowers_model_{model_name}.tflite\", \"wb\") as f:\n",
        "  f.write(lite_model_content)\n",
        "print(\"Wrote %sTFLite model of %d bytes.\" %\n",
        "      (\"optimized \" if optimize_lite_model else \"\", len(lite_model_content)))"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Wrote optimized TFLite model of 7098720 bytes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_wqEmD0xIqeG"
      },
      "source": [
        "interpreter = tf.lite.Interpreter(model_content=lite_model_content)\n",
        "# This little helper wraps the TF Lite interpreter as a numpy-to-numpy function.\n",
        "def lite_model(images):\n",
        "  interpreter.allocate_tensors()\n",
        "  interpreter.set_tensor(interpreter.get_input_details()[0]['index'], images)\n",
        "  interpreter.invoke()\n",
        "  return interpreter.get_tensor(interpreter.get_output_details()[0]['index'])"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JMMK-fZrKrk8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f5e205ee-42da-4041-b397-26408ad78b88"
      },
      "source": [
        "#@markdown For rapid experimentation, start with a moderate number of examples.\n",
        "num_eval_examples = 50  #@param {type:\"slider\", min:0, max:700}\n",
        "eval_dataset = ((image, label)  # TFLite expects batch size 1.\n",
        "                for batch in train_generator\n",
        "                for (image, label) in zip(*batch))\n",
        "count = 0\n",
        "count_lite_tf_agree = 0\n",
        "count_lite_correct = 0\n",
        "for image, label in eval_dataset:\n",
        "  probs_lite = lite_model(image[None, ...])[0]\n",
        "  probs_tf = model(image[None, ...]).numpy()[0]\n",
        "  y_lite = np.argmax(probs_lite)\n",
        "  y_tf = np.argmax(probs_tf)\n",
        "  y_true = np.argmax(label)\n",
        "  count +=1\n",
        "  if y_lite == y_tf: count_lite_tf_agree += 1\n",
        "  if y_lite == y_true: count_lite_correct += 1\n",
        "  if count >= num_eval_examples: break\n",
        "print(\"TF Lite model agrees with original model on %d of %d examples (%g%%).\" %\n",
        "      (count_lite_tf_agree, count, 100.0 * count_lite_tf_agree / count))\n",
        "print(\"TF Lite model is accurate on %d of %d examples (%g%%).\" %\n",
        "      (count_lite_correct, count, 100.0 * count_lite_correct / count))"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "TF Lite model agrees with original model on 49 of 50 examples (98%).\n",
            "TF Lite model is accurate on 48 of 50 examples (96%).\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}
